Bibliographic record
Abstract
The idea of resource scarcity permeates health ethics and health policy analysis in various contexts. However, health ethics inquiry seldom asks-as it should-why some settings are 'resource-scarce' and others not. In this article I describe interrogating scarcity as a strategy for inquiry into questions of resource allocation within a single political jurisdiction and, in particular, as an approach to the issue of global health justice in an interconnected world. I demonstrate its relevance to the situation of low- and middle-income countries (LMICs) with brief descriptions of four elements of contemporary globalization: trade agreements; the worldwide financial marketplace and capital flight; structural adjustment; imperial geopolitics and foreign policy. This demonstration involves not only health care, but also social determinants of health. Finally, I argue that interrogating scarcity provides the basis for a new, critical approach to health policy at the interface of ethics and the social sciences, with specific reference to market fundamentalism as the value system underlying contemporary globalization.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.039 | 0.055 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.014 | 0.184 |
| Scholarly communication | 0.023 | 0.073 |
| Open science | 0.006 | 0.019 |
| Research integrity | 0.014 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".